Object-based change detection in wind storm-damaged forest using high-resolution multispectral images

International Journal of Remote Sensing

Volumn 35, Issue 13, 2014, Pages 4758-4777

  Chehata, N ^a,b   Orny, C ^a,c   Boukir, S ^a   Guyon, D ^c   Wigneron, J P ^c  

^a UNIVERSITÉ DE BORDEAUX   (France)

^b UMR LISAH   (France)

^c BORDEAUX SCIENCES AGRO   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COST EFFECTIVENESS; DAMAGE DETECTION; DISASTER PREVENTION; DISASTERS; FORESTRY; IMAGE SEGMENTATION; OBJECT DETECTION; REMOTE SENSING; RISK ASSESSMENT; SATELLITE IMAGERY;

AUTOMATIC FEATURE SELECTION; CLASSIFICATION ACCURACY; CLASSIFICATION PROCESS; GROUND INVESTIGATION; HIGH SPATIAL RESOLUTION; MEAN SHIFT ALGORITHM; OBJECT BASED CHANGE DETECTIONS; REMOTE SENSING TECHNIQUES;

FEATURE EXTRACTION;

ALGORITHM; CALIBRATION; DETECTION METHOD; ECOSYSTEM APPROACH; EFFICIENCY MEASUREMENT; FOREST COVER; FORMOSAT-2; FRAGMENTATION; MULTISPECTRAL IMAGE; NATURAL DISASTER; SPATIAL RESOLUTION; STORM DAMAGE;

DAMAGE; FORESTRY; IMAGE ANALYSIS; REMOTE SENSING; RISK ASSESSMENT; SATELLITES;

PINUS PINASTER;

EID: 84905029227     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2014.930199     Document Type: Article

References (47)

1. Benz, U. C., P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen. 2004. "Multi-Resolution, Object-Oriented Fuzzy Analysis of Remote Sensing Data for Gis-Ready Information." ISPRS Journal of Photogrammetry and Remote Sensing 58 (3-4): 239-258. doi:10.1016/j.isprsjprs.2003.10.002.
2. Blaschke, T. 2010. "Object Based Image Analysis for Remote Sensing." ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 2-16. doi:10.1016/j.isprsjprs.2009.06.004.
3. Chehata, N., C. Orny, S. Boukir, and D. Guyon. 2011. "Object-Based Forest Change Detection Using High Resolution Satellite Images." In PIA11, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII, edited by U. Stilla, F. Rottensteiner, H. Mayer, B. Jutzi, and M. Butenuth, Vol. 3/W22, Munich, October 5-7, 49-55.
4. Clandillon, S., H. Yesou, and C. Meyer. 2003. "Benefits of SPOT 5 HR and VHR Data for Forest Management and Windfall Damage Mapping." In IEEE International Geoscience and Remote Sensing Symposium, IGARSS '03, Vol. 5, Toulouse, 3079-3081. IEEE. doi:10.1109/IGARSS.2003.1294689.
5. Comaniciu, D., and P. Meer. 2002. "Mean Shift: Arobust Approach toward Feature Space Analysis." IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (5): 603-619. doi:10.1109/34.1000236.
6. Conchedda, G., L. Durieux, and P. Mayaux 2008. "An Object-Based Method for Mapping and Change Analysis in Mangrove Ecosystems." ISPRS Journal of Photogrammetry and Remote Sensing 63 (5): 578-589. Remote Sensing of the Coastal Ecosystems Special Issue. doi:10.1016/j.isprsjprs.2008.04.002.
7. Cucchi, V., C. Meredieu, A. Stokes, F. Coligny, J. Suarez, and B. A. Gardiner. 2005. "Modelling the Windthrow Risk for Simulated Forest Stands of Maritime Pine (Pinus Pinaster Ait.)." Forest Ecology and Management 213: 184-196. doi:10.1016/j.foreco.2005.03.019.
8. Desclée, B., P. Bogaert, and P. Defourny. 2006. "Forest Change Detection by Statistical Object-Based Method." Remote Sensing of Environment 102 (1-2): 1-11. doi:10.1016/j.rse.2006.01.013.
9. Duda, R. O., P. E. Hart, and D. G. Stork. 2001. Pattern Classification. 2nd ed. New York: Wiley-Interscience.
10. Franklin, S. E., R. H. Waring, R. W. McCreight, W. B. Cohen, and M. Fiorella. 1995. "Aerial and Satellite Sensor Detection and Classification of Western Spruce Budworm Defoliation in a Subalpine Forest. Canadian Journal of Remote Sensing 21: 299-308.
11. Fraser, R. H., A. Abuelgasim, and R. Latifovic. 2005. "A Method for Detecting Large-Scale Forest Cover Change Using Coarse Spatial Resolution Imagery." Remote Sensing of Environment 95 (4): 414-427. doi:10.1016/j.rse.2004.12.014.
12. Fukunaga, K., and L. Hostetler. 1975. "The Estimation of the Gradient of a Density Function, with Applications in Pattern Recognition." IEEE Transactions on Information Theory 21: 32-40. doi:10.1109/TIT.1975.1055330.
13. Garestier, F., P. Dubois-Fernandez, D. Guyon, and T. Le Toan. 2009. "Forest Biophysical Parameter Estimation Using L- and P-Band Polarimetric SAR Data." IEEE Transactions on Geoscience and Remote Sensing 47 (10): 3379-3388. doi:10.1109/TGRS.2009.2022947.
14. Guyon, D., I. Champion, C. Meredieu, A. Kruszewski, and T. Labbe. 2005. Final Report - Work Package 1-1 "Ground Data Base ", April 2005. Technical Report, INRA/Egyptsar04/IC01 and ESTEC-European Space Agency, Contract 18507/04, 18.
15. Guyon, D., G. Courrier, and P. Berbigier. 2001. "Sensitivity Analysis of Coniferous Forest Reflectance with Canopy Structure and Undergrowth Characteristics from Satellite Data and Modelling (Case Study: Landes Maritime Pine Forest)." In 8th International Symposium "Physical Measurements and Signatures in Remote Sensing", edited by CNES, Aussois, January, 387-392.
16. Haralick, R. M., K. Shanmugam, and I. Dinstein. 1973. "Textural Features for Image Classification." IEEE Transactions on Systems, Man, and Cybernetics 3: 610-621. doi:10.1109/TSMC.1973.4309314.
17. Hayes, D. J., and W. B. Cohen. 2007. "Spatial, Spectral and Temporal Patterns of Tropical Forest Cover Change as Observed with Multiple Scales of Optical Satellite Data." Remote Sensing of Environment 106 (1): 1-16. doi:10.1016/j.rse.2006.07.002.
18. Huang, C., K. Song, S. Kim, J. R. G. Townshend, P. Davis, J. G. Masek, and S. N. Goward. 2008. "Use of a Dark Object Concept and Support Vector Machines to Automate Forest Cover Change Analysis." Remote Sensing of Environment 112 (3): 970-985. doi:10.1016/j.rse.2007.07.023.
19. Im, J., and J. R. Jensen. 2005. "A Change Detection Model Based on Neighborhood Correlation Image Analysis and Decision Tree Classification." Remote Sensing of Environment 99 (3): 326-340. doi:10.1016/j.rse.2005.09.008.
20. Johansen, K., L. A. Arroyo, S. Phinn, C. Witte, R. J. Kauth, and G. S. Thomas. 2010. "Comparison of Geo-Object Based and Pixel-Based Change Detection of Riparian Environments Using High Spatial Resolution Multi-Spectral Imagery." Photogrammetric Engineering and Remote Sensing 76 (2): 123-136. doi:10.14358/PERS.76.2.123.
21. Johansen, K., N. C. Coops, S. E. Gergel, and Y. Stange. 2007. "Application of High Spatial Resolution Satellite Imagery for Riparian and Forest Ecosystem Classification." Remote Sensing of Environment 110 (1): 29-44. doi:10.1016/j.rse.2007.02.014.
22. Jonikavičius, D., and G. Mozgeris. 2013. "Rapid Assessment of Wind Storm-Caused Forest Damage Using Satellite Images and Stand-Wise Forest Inventory Data." iforest 6: 150-155. doi:10.3832/ifor0715-006.
23. Kayitakire, F., C. Hamel, and P. Defourny. 2006. "Retrieving Forest Structure Variables Based on Image Texture Analysis and IKONOS-2 Imagery." Remote Sensing of Environment 102: 390-401. doi:10.1016/j.rse.2006.02.022.
24. Kennedy, R. E., P. A. Townsend, J. E. Gross, W. B. Cohen, P. Bolstad, Y. Q. Wang, and P. Adams. 2009. "Remote Sensing Change Detection Tools for Natural Resource Managers: Understanding Concepts and Tradeoffs in the Design of Landscape Monitoring Projects." Remote Sensing of Environment 113 (7): 1382-1396. doi:10.1016/j.rse.2008.07.018.
25. Kim, M., M. Madden, and T. Warner. 2008. "Estimation of Optimal Image Object Size for the Segmentation of Forest Stands with Multispectral IKONOS Imagery." In Object-Based Image Analysis, edited by T. Blaschke, S. Lang, and G. J. Hay, 291-307. Lecture Notes in Geoinfor-mation and Cartography. Berlin: Springer.
26. King, D. J., I. Olthof, P. K. E. Pellikka, E. D. Seed, and C. Butson. 2005. "Modelling and Mapping Damage to Forests from an Ice Storm Using Remote Sensing and Environmental Data." Natural Hazards 35: 321-342. doi:10.1007/s11069-004-1795-4.
27. Lamonaca, A., P. Corona, and A. Barbati. 2008. "Exploring Forest Structural Complexity by Multi-Scale Segmentation of VHR Imagery." Remote Sensing of Environment 112 (6): 2839-2849. doi:10.1016/j.rse.2008.01.017.
28. Liu, D., K. Song, J. R. G. Townshend, and P. Gong. 2008. "Using Local Transition Probability Models in Markov Random Fields for Forest Change Detection." Remote Sensing of Environment 112 (5): 2222-2231. Earth Observations for Terrestrial Biodiversity and Ecosystems Special Issue. doi:10.1016/j.rse.2007.10.002.
29. Mäkelä, H., and A. Pekkarinen. 2001. "Estimation of Timber Volume at the Sample Plot Level by Means of Image Segmentation and Landsat TM Imagery." Remote Sensing of Environment 77: 66-75. doi:10.1016/S0034-4257(01)00194-8.
30. Mallinis, G., N. Koutsias, M. Tsakiri-Strati, and M. Karteris. 2008. "Object-Based Classification Using Quickbird Imagery for Delineating Forest Vegetation Polygons in a Mediterranean Test Site." ISPRS Journal of Photogrammetry and Remote Sensing 63 (2): 237-250. doi:10.1016/j.isprsjprs.2007.08.007.
31. McRoberts, R. E., and B. F. Walters. 2012. "Statistical Inference for Remote Sensing-Based Estimates of Net Deforestation." Remote Sensing of Environment 124: 394-401. doi:10.1016/j.rse.2012.05.011.
32. Meyer, C., P. Geldreich, and H. Yesou. 2001. "Apports des Données Simulées SPOT5 Pour l' Évaluation Des Dégâts De Tempête Dans La Forêt. Cas De La Foret De Haguenau (Alsace, France)." In Bulletin de la Société Française de Photogrammétrie et de Télédétection, No. 164-165 (2001-4/2002-1): 162-173.
33. Olthof, I., D. J. King, and R. A. Lautenschlager. 2004. "Mapping Deciduous Forest Ice Storm Damage Using Landsat and Environmental Data." Remote Sensing of Environment 89: 484-496. doi:10.1016/j.rse.2003.11.010.
34. Orny, C., N. Chehata, S. Boukir, and D. Guyon. 2010. Characterization of Maritime Pine Forest Structure Changes with VHR Satellite Imagery: Application to the 24th January 2009 Windfall Damages Cartography. Technical Report. Toulouse: CNES.
35. Otsu, N. 1979. "A Threshold Selection Method from Gray-Level Histograms." IEEE Transactions on Systems, Man and Cybernetics 9: 62-66. doi:10.1109/TSMC.1979.4310076.
36. Ozdarici, O. A., and Z. Akyurek. 2012. "A Segment-Based Approach to Classify Agricultural Lands by Using Multi-Temporal Optical and Microwave Data." International Journal of Remote Sensing 33 (22): 7184-7204. doi:10.1080/01431161.2012.700423.
37. Pasher, J., and D. J. King. 2009. "Mapping Dead Wood Distribution in a Temperate Hardwood Forest Using High Resolution Airborne Imagery." Forest Ecology and Management 258: 1536-1548. doi:10.1016/j.foreco.2009.07.009.
38. Ruiz, L. A., A. Fdez-sarria, and J. A. Recio. 2004. "Texture Feature Extraction for Classification of Remote Sensing Data Using Wavelet Decomposition: A Comparative Study." International Archives of Photogrammetry and Remote Sensing XXXV: 1682-1750.
39. Schwarz, M., C. Steinmeier, and L. Waser. 2001. "Detection of Storm Losses in Alpine Forest Areas by Different Methodic Approaches Using High Resolution Satellite Data." In Proceedings of the 21st EARSeL Symposium: Observing Our Environment from Space: New Solutions for a New Millenium, 251-257.
40. St-Louis, V., A. M. Pidgeon, V. C. Radeloff, T. J. Hawbaker, and M. K. Clayton. 2006. "Highresolution Image Texture as a Predictor of Bird Species Richness." Remote Sensing of Environment 105: 299-312. doi:10.1016/j.rse.2006.07.003.
41. Trias-Sanz, R., G. Stamon, and J. Louchet. 2008. "Using Colour, Texture, and Hierarchial Segmentation for High-Resolution Remote Sensing." ISPRS Journal of Photogrammetry and Remote Sensing 63: 156-168. doi:10.1016/j.isprsjprs.2007.08.005.
42. Tuominen, S., and A. Pekkarinen. 2005. "Performance of Different Spectral and Textural Aerial Photograph Features in Multi-Source Forest Inventory." Remote Sensing of Environment 94: 256-268. doi:10.1016/j.rse.2004.10.001.
43. Vibrans, A. C., R. E. McRoberts, P. Moser, and A. L. Nicoletti. 2013. "Using Satellite Image-Based Maps and Ground Inventory Data to Estimate the Area of the Remaining Atlantic Forest in the Brazilian State of Santa Catarina." Remote Sensing of Environment 130: 87-95. doi:10.1016/j.rse.2012.10.023.
44. Wang, W., J. J. Qu, X. Hao, Y. Liu, and J. A. Stanturf. 2010. "Post-Hurricane Forest Damage Assessment Using Satellite Remote Sensing." Agricultural and Forest Meteorology 150: 122-132. doi:10.1016/j.agrformet.2009.09.009.
45. Wang, Y., Y. S. Soh, and H. Shultz. 2006. "Individual Tree Crown Segmentation in Aerial Forestry Images by Mean Shift Clustering and Graph-Based Cluster Merging." International Journal of Computer Science and Network Security 6 (11): 40-45.
46. Wang, F., and Y. J. Xu. 2010. "Comparison of Remote Sensing Change Detection Techniques for Assessing Hurricane Damage to Forests." Environmental Monitoring and Assessment 162: 311-326. doi:10.1007/s10661-009-0798-8.
47. Wulder, M. A., J. C. White, N. C. Coops, and C. R. Butson. 2008. "Multi-Temporal Analysis of High Spatial Resolution Imagery for Disturbance Monitoring." Remote Sensing of Environment 112 (6): 2729-2740. doi:10.1016/j.rse.2008.01.010.